In modern days, various advancements in the field of information technology have provided numerous tools and applications, such as recommendation systems, to customers that intend to buy products and/or services via online stores and/or physical stores. Such recommendation systems cater to a section of customers who still prefer shopping at physical stores that provide physical infrastructure for showcasing various products provided by different vendors.
Various techniques, such as text messaging, have been devised to implement such recommendation systems so that a single recommendation is provided to the customers regarding products, offers, and deals at such physical stores. However, in certain scenarios, the text messages are spam and may not cater to the needs of the customers. Further, such text messages may not be related to the personas of the customers. Furthermore, hectic lifestyles of the customers and massive expansion of available products and stores have tremendously increased the struggle of the customers in deciding what to buy, in which stores to buy, and what route to take to reach such physical stores. Therefore a dynamic and comprehensive recommendation system is required that matches the needs of the customers by taking into account their shopping personas and various constraints.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to a person having ordinary skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings